Toward a Symbolic Representation of Intensity Changes in Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Two-plus-one-dimensional differential geometry
VIP '94 The international conference on volume image processing on Volume image processing
The multiscale medial axis and its applications in image registration
VIP '94 The international conference on volume image processing on Volume image processing
Zoom-invariant vision of figural shape: the mathematics of cores
Computer Vision and Image Understanding
Edge Detection and Ridge Detection with Automatic Scale Selection
International Journal of Computer Vision
SCALE-SPACE '97 Proceedings of the First International Conference on Scale-Space Theory in Computer Vision
Detection of Critical Structures in Scale Space
SCALE-SPACE '99 Proceedings of the Second International Conference on Scale-Space Theories in Computer Vision
Multiscale detection of curvilinear structures in 2-D and 3-D image data
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Classification of silhouettes using contour fragments
Computer Vision and Image Understanding
Real-time scale selection in hybrid multi-scale representations
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
Automation of hessian-based tubularity measure response function in 3D biomedical images
Journal of Biomedical Imaging - Special issue on modern mathematics in biomedical imaging
Shape categorization using string kernels
SSPR'06/SPR'06 Proceedings of the 2006 joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
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A method to automatically select locally appropriate scales for feature detection, proposed by Lindeberg [8], [9], involves choosing a so-called 驴-parameter. The implications of the choice of 驴-parameter are studied and it is demonstrated that different values of 驴 can lead to qualitatively different features being detected. As an example the range of 驴-values is determined such that a second derivative of Gaussian filter kernel detects ridges but not edges. Some results of this relatively simple ridge detector are shown for two-dimensional images.